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Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms

IEEE Transactions on Geoscience and Remote Sensing

By:
, ,
DOI: 10.1109/TGRS.2011.2164087

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Abstract

The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Development of the Landsat Data Continuity Mission Cloud Cover Assessment Algorithms
Series title:
IEEE Transactions on Geoscience and Remote Sensing
DOI:
10.1109/TGRS.2011.2164087
Volume
50
Issue:
4
Year Published:
2012
Language:
English
Publisher location:
Reston, VA
Contributing office(s):
Earth Resources Observation and Science (EROS) Center
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
IEEE Transactions on Geoscience and Remote Sensing
First page:
1140
Last page:
1154
Country:
United States